[Editor’s note: “As we try to integrate highly resolved data into existing GIS, the errors in legacy data will become more apparent.” Jeff outlines the problem through his experience at the BLM in Oregon. Jeff is also responsible for early “bump mapping” of digital terrain models (DEMs).]
Republished from the ESRI ArcUser Winter 2010.
By Jeffery S. Nighbert, U.S. Bureau of Land Management
The ability to obtain precise information is nothing new. With great patience and skill, mapmakers and land surveyors have long been able to create information with an impressive level of accuracy. However, today the ability to determine and view locations with submeter accuracy is now in the hands of millions of people. Commonly available high-resolution digital terrain and aerial imagery, coupled with GPS-enabled handheld devices, powerful computers, and Web technology, is changing the quality, utility, and expectations of GIS to serve society on a grand scale. This accuracy and precision revolution has raised the bar for GIS quite high. This pervasive capability will be the driver for the next iteration of GIS and the professionals who operate them.
When I say there is a “revolution” going on in GIS, I am referring to the change in the fundamental accuracy and precision kernel of commonly used geographic data brought about by new technologies previously mentioned. For many ArcGIS users, this kernel used to be about 10 meters or 40 feet at a scale of 1:24,000. With today’s technologies (and those in the future), GIS will be using data with 1-meter and submeter accuracy and precision. There are probably GIS departments—in a large city or metro area—where this standard is already in place. However, this level of detail is far from the case in natural resource management agencies such as Bureau of Land Management (BLM) or the United States Forest Service. But as lidar, GPS, and high-resolution imagery begin to proliferate standard sources for “ground” locations, GIS professionals will begin to feel the consequences in three areas: data quality, analytic methods, and hardware and software.